儿科阻塞性睡眠呼吸暂停的诊断方式:一篇综述文章
1Department of Pediatrics, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Sleep medicine
|December 19, 2025
概括
像问卷和智能手机视频分析等替代工具可以有效地选儿科阻塞性睡眠呼吸暂停 (OSA). 自动氧测和人工智能模型提供准确的诊断,当多睡眠学是不可访问的.
科学领域:
- 儿科睡眠医学 儿科睡眠医学
- 诊断技术 诊断技术 诊断技术
- 呼吸系统医学 呼吸系统医学
背景情况:
- 儿童阻塞性睡眠呼吸暂停 (OSA) 影响大约3%的儿童,导致显著的神经认知,行为和心血管问题.
- 聚睡眠学 (PSG) 是标准的诊断方法,但往往受到了可访问性的限制.
- 本综述批判性地检查了小儿OSA的替代诊断工具,评估了它们的准确性,可行性和临床实用性.
研究的目的:
- 系统地审查和综合关于儿科阻塞性睡眠呼吸暂停 (OSA) 替代诊断工具的证据.
- 评估非PSG诊断方法在儿童中的准确性,可行性和临床适用性.
- 确定最佳的诊断途径,用于儿科OSA当PSG是不容易获得.
主要方法:
- 通过使用主要科学数据库 (PubMed,Scopus,Web of Science) 进行了系统叙事混合审查,直到2025年7月.
- 研究包括0-18岁的儿童,使用问卷,氧度计,便携式显示器,AI/ML模型或智能手机视频分析进行诊断,与PSG进行比较.
- 确定并评估了五种主要类别的替代诊断模式.
主要成果:
- 儿童睡眠问卷 (PSQ) 和智能手机视频分析 (VAPS) 等查工具对OSA检测显示出高灵敏度 (73-96%).
- 算法增强的脉冲氧计显示,对于中度至重度的OSA,其诊断准确度很好 (AUC为0.90-0.97,灵敏度/特异性>85-90%) .
- 机器学习模型和可穿戴设备接近了PSG级别的性能,通过将问卷和氧计结合起来进行逐步选,证明是最佳的.
结论:
- 问卷和智能手机视频分析作为有效的查工具,用于儿童OSA在资源有限的设置.
- 自动氧测和机器学习模型为中度至重度儿科OSA提供了可行的诊断替代方案.
- 实施多层次的诊断途径,整合各种工具,可以提高检测率,减少对PSG的依赖.
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